code-to-requirement-analyser

This skill appears to implement the advertised code-analysis and knowledge-graph features and stores results locally, but there are a few things to check before using it: - Inspect and run in a sandbox: review the bundled Python files (especially parser modules and CLI) and, if possible, run the tool in an isolated environment (container or VM) before pointing it at sensitive repositories. - Confirm storage locations: SKILL.md defaults to ~/.openclaw for cache and knowledge; if you don't want outputs stored in your home, set KNOWLEDGE_BASE_PATH and CACHE_DIR to a dedicated directory. - Optional LLM usage: the SKILL.md suggests installing openai and using LLM_API_KEY for deeper analysis. Do not provide any production or sensitive API keys unless you trust the code — supplying an LLM API key enables network calls and could transmit analysis payloads externally. - Be cautious with running helper scripts: fix_setup.sh creates files and placeholder parser implementations; review its contents before executing it. - Verify imports execute safely: the CLI imports parser modules at startup; ensure those modules contain no unexpected top-level side effects. If you want greater assurance, ask the skill author for a provenance/origin (source repo) or run a full static review of all included files. The current assessment is 'suspicious' because of metadata vs. SKILL.md inconsistencies and optional network-capable behavior (LLM integration), not because of obvious malicious code.